49 search results - page 7 / 10 » Model-based Policy Gradient Reinforcement Learning |
NIPS
2008
13 years 9 months ago
2008
Many motor skills in humanoid robotics can be learned using parametrized motor primitives as done in imitation learning. However, most interesting motor learning problems are high...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
ICANN
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
ICRA
2010
IEEE
13 years 6 months ago
2010
IEEE
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
NN
2010
Springer
13 years 6 months ago
2010
Springer
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...